Statistical Analysis of Noise in MRI

Modeling, Filtering and Estimation

  • Santiago Aja-Fernández
  • Gonzalo Vegas-Sánchez-Ferrero

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
    Pages 1-6
  3. Noise Models and the Noise Analysis Problem

    1. Front Matter
      Pages 7-7
    2. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 9-29
    3. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 31-71
    4. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 73-88
    5. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 89-119
  4. Noise Analysis in Nonaccelerated Acquisitions

    1. Front Matter
      Pages 121-121
    2. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 123-140
    3. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 141-171
    4. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 173-186
    5. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 187-207
  5. Noise Estimators in pMRI

    1. Front Matter
      Pages 209-209
    2. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 211-228
    3. Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 229-274
  6. Back Matter
    Pages 275-327

About this book

Introduction

This unique text/reference presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques drawn from more than ten years of research in this area.

Topics and features:

  • Provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques
  • Describes noise and signal estimation for MRI from a statistical signal processing perspective
  • Surveys the different methods to remove noise in MRI acquisitions, under different approaches and from a practical point of view
  • Reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions
  • Examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal
  • Includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets

This practically-focused work serves as a reference manual for researchers dealing with signal processing in MRI acquisitions, and is also suitable as a textbook for postgraduate students in engineering with an interest in medical image processing.

Dr. Santiago Aja-Fernández is an Associate Professor at the School of Telecommunications of the University of Valladolid, Spain. His other publications include the Springer title Tensors in Image Processing and Computer Vision. Dr. Gonzalo Vegas-Sánchez-Ferrero is a Research Fellow at Brigham and Women’s Hospital, and in the Applied Chest Imaging Laboratory of Harvard Medical School, Boston, MA, USA.

Keywords

MRI Noise Modeling Signal Processing Parallel Imaging Estimation

Authors and affiliations

  • Santiago Aja-Fernández
    • 1
  • Gonzalo Vegas-Sánchez-Ferrero
    • 2
  1. 1. University of ValladolidValladolidSpain
  2. 2.Harvard Medical SchoolBostonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-39934-8
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-39933-1
  • Online ISBN 978-3-319-39934-8
  • About this book